Development and validation of a dynamic 48-hour in-hospital mortality risk stratification for COVID-19 in a UK teaching hospital: a retrospective cohort study


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Abstract

jats:secjats:titleObjectives</jats:title>jats:pTo develop a disease stratification model for COVID-19 that updates according to changes in a patient’s condition while in hospital to facilitate patient management and resource allocation.</jats:p></jats:sec>jats:secjats:titleDesign</jats:title>jats:pIn this retrospective cohort study, we adopted a landmarking approach to dynamic prediction of all-cause in-hospital mortality over the next 48 hours. We accounted for informative predictor missingness and selected predictors using penalised regression.</jats:p></jats:sec>jats:secjats:titleSetting</jats:title>jats:pAll data used in this study were obtained from a single UK teaching hospital.</jats:p></jats:sec>jats:secjats:titleParticipants</jats:title>jats:pWe developed the model using 473 consecutive patients with COVID-19 presenting to a UK hospital between 1 March 2020 and 12 September 2020; and temporally validated using data on 1119 patients presenting between 13 September 2020 and 17 March 2021.</jats:p></jats:sec>jats:secjats:titlePrimary and secondary outcome measures</jats:title>jats:pThe primary outcome is all-cause in-hospital mortality within 48 hours of the prediction time. We accounted for the competing risks of discharge from hospital alive and transfer to a tertiary intensive care unit for extracorporeal membrane oxygenation.</jats:p></jats:sec>jats:secjats:titleResults</jats:title>jats:pOur final model includes age, Clinical Frailty Scale score, heart rate, respiratory rate, oxygen saturation/fractional inspired oxygen ratio, white cell count, presence of acidosis (pH <7.35) and interleukin-6. Internal validation achieved an area under the receiver operating characteristic (AUROC) of 0.90 (95% CI 0.87 to 0.93) and temporal validation gave an AUROC of 0.86 (95% CI 0.83 to 0.88).</jats:p></jats:sec>jats:secjats:titleConclusions</jats:title>jats:pOur model incorporates both static risk factors (eg, age) and evolving clinical and laboratory data, to provide a dynamic risk prediction model that adapts to both sudden and gradual changes in an individual patient’s clinical condition. On successful external validation, the model has the potential to be a powerful clinical risk assessment tool.</jats:p></jats:sec>jats:secjats:titleTrial registration</jats:title>jats:pThe study is registered as ‘researchregistry5464’ on the Research Registry (<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="www.researchregistry.com">www.researchregistry.com</jats:ext-link>).</jats:p></jats:sec>

Description
Keywords
Epidemiology, 1506, 2474, 1692, COVID-19, epidemiology, risk management, statistics & research methods
Journal Title
BMJ Open
Conference Name
Journal ISSN
2044-6055
2044-6055
Volume Title
Publisher
BMJ
Sponsorship
National Institute for Health Research (IS-BRC-1215-20014)
MRC (unknown)
Cambridge University Hospitals NHS Foundation Trust (CUH) (BRC)